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Behind every informed decision lies a sound prediction. Despite the increasing availability of “big” data and recent advances in algorithmic predictions, the most important strategic decisions still require human judgment. When relevant information is dispersed across people with varying knowledge and expertise, organizations need to address the key questions of crowd-sourced prediction and decision-making:

  • Who are the experts in the crowd?
  • What is the best way to aggregate the experts’ judgments?
  • How can we prevent bias, “gaming,” and groupthink?

This seminar equips the participants with the tools required to answer these questions, allowing them to turn the wisdom of the crowds into superior decisions for the organisation.

Content overview

  • Designing corporate prediction systems
  • Incentivizing effort and truth revelation
  • Recovering truth even if the majority is wrong
  • Identifying experts in a crowd
  • When do algorithms (not) beat intuition?
  • Live simulations to uncover (and fix) human judgment bias
  • Case discussions of real-world prediction systems

Your Experts

Prof. Dr. Mirko Kremer

is Professor of Supply Chain Management at the Frankfurt School of Finance & Management. He received his PhD from the University of Mannheim, and has previously taught at the Pennsylvania State University, INSEAD, Kellogg School of Management, and London Business School. Mirko's research focuses on the impact of managerial and customer (mis)behavior on the performance and design of Operations systems. His work on judgmental forecasting has been published in leading international journals.

Prof. Dr. Jens Witkowski

is Assistant Professor of Information Systems at Frankfurt School of Finance & Management. His research focuses on the intersection of data science and economics, with an emphasis on eliciting, aggregating, and evaluating crowd-sourced information. Jens has worked extensively on theoretical and empirical approaches to peer prediction and probabilistic forecasting. Before joining Frankfurt School, he held postdoctoral positions in the Good Judgment Project at the University of Pennsylvania and with the Institute for Machine Learning at ETH Zurich. From 2010–2014, Jens was a Fellow of the School of Engineering and Applied Sciences at Harvard University, where he worked on robust peer prediction mechanisms with David C. Parkes. Jens received his Ph.D. (2014) and Master’s (2009) degrees in Computer Science from Albert-Ludwigs-Universität Freiburg, Germany.

Key Facts

Target group

Managers, Directors

Methodology

Case Studies

Duration

2 days

Day 1: 9:30 am - 5:30 pm

Day 2: 9 am - 5 pm

Registration as PDF

Coming soon

Dates and Online-Registration

Expert advice

Organisational advice

Customised Programmes

We would be glad to advise you and create a tailor-made company offer on request. Find out more about our corporate offers or write us an email.

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